GIS Based Stereoscopic Visualization Technique for Weather Radar Data

Abstract:

As rainfall characteristic is more quixotic and localized, it is important to provide a prompt and accurate warning for public. To monitor localized heavy rainfall, a reliable disaster monitoring system with advanced remote observation technology and high-precision display system is needed. To advance even more accurate weather monitoring using weather radar, there have been growing concerns regarding the real-time changes of mapping radar observations on geographical coordinate systems along with the visualization and display methods of radar data based on spatial interpolation techniques and geographical information system (GIS). Currently, the method of simultaneously displaying GIS and radar data is widely used to synchronize the radar and ground systems accurately, and the method of displaying radar data in the 2D GIS coordinate system has been extensively used as the display method for providing weather information from weather radar. This paper proposes a realistic 3D weather radar data display technique with higher spatiotemporal resolution, which is based on the integration of 3D image processing and GIS interaction. This method is focused on stereoscopic visualization, while conventional radar image display works are based on flat or two-dimensional interpretation. Furthermore, using the proposed technique, the atmospheric change at each moment can be observed three-dimensionally at various geological locations simultaneously. Simulation results indicate that 3D display of weather radar data can be performed in real time. One merit of the proposed technique is that it can provide intuitive understanding of the influence of beam blockage by topography. Through an exact matching each 3D modeled radar beam with 3D GIS map, we can find out the terrain masked areas and accordingly it facilitates the precipitation correction from QPE underestimation caused by ground clutter filtering. It can also be expected that more accurate short-term forecasting will be possible using stereoscopic observation of weather phenomena changes.